code: def test_kalman_given_kf(self):
      nfoursid_ss = state_space.StateSpace(
          a=np.eye(2),
          b=np.ones((2, 1)),
          c=np.ones((1, 2)),
          d=np.ones((1, 1)),
      )
      nfoursid_kf = kalman.Kalman(nfoursid_ss, np.ones((3, 3)) * 0.1)
      kf = KalmanFilter(dim_x=1, kf=nfoursid_kf)
  
      series = tg.sine_timeseries(length=30, value_frequency=0.1)
  
      prediction = kf.filter(series, covariates=-series.copy())
  
      assert kf.dim_u == 1
      assert kf.dim_x == 2
      assert prediction.width == 1
      assert prediction.n_samples == 1
  
imports: import numpy
  import pandas
  from nfoursid import kalman, state_space
  from sklearn.gaussian_process.kernels import RBF, ExpSineSquared
  from darts import TimeSeries
  from darts.metrics import rmse
  from darts.models.filtering.gaussian_process_filter import GaussianProcessFilter
  from darts.models.filtering.kalman_filter import KalmanFilter
  from darts.models.filtering.moving_average_filter import MovingAverageFilter
  from darts.utils import timeseries_generation
label_desc: Use image node_id 7 for calling the TestKalmanFilter obj's underlying member method code with example usage: obj.test_kalman_given_kf() without return types